Machine Learning in the Prediction of Venous Thromboembolism: Systematic Review and Meta-Analysis

ML has been shown to effectively predict VTE in patients. However, a high risk of bias was identified in most of the included studies (18/27, 67%), primarily due to shortcomings in handling missing data and reporting the study design. Consequently, future research must prioritize external validation and address methodological rigor to facilitate the translation of these models into routine clinical practice.